Bone SPECT image reconstruction using deconvolution and wavelet transformation: Development, performance assessment and comparison in phantom and patient study with standard OSEM and resolution recovery algorithm

被引:5
作者
Ptacek, Jaroslav [1 ,2 ]
Henzlova, Lenka [1 ]
Koranda, Pavel [1 ]
机构
[1] Univ Hosp Olomouc, Dept Nucl Med, Olomouc 77520, Czech Republic
[2] Univ Hosp Olomouc, Dept Med Phys & Radiat Protect, Olomouc 77520, Czech Republic
来源
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS | 2014年 / 30卷 / 07期
关键词
Deconvolution; Logarithmic image processing; Wavelet denoising; EMISSION-TOMOGRAPHY; PROCESSING MODEL; ITERATIVE RECONSTRUCTION; MULTIRESOLUTION ANALYSIS; AGREEMENT; DOMAIN;
D O I
10.1016/j.ejmp.2014.06.002
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: The aim of this work was to introduce a new algorithm for image reconstruction in bone SPECT and to compare its performances with a commercially available standard OSEM and resolution recovery (RR) reconstruction. Materials and methods: The algorithm was built applying the Lucy-Richardson deconvolution adn logarithmic image processing to the projections. A modification of the coefficients of wavelet decomposition was used to suppress the noise. The comparison with vendor software was performed both in a phantom study, using Signal-to-Noise ratio (SNR), Signal-to-Background ratio (SBR), spatial resolution and in clinical studies, by visual assessment of changes in contrast, spatial resolution and lesion detectability. Results: A change in the SNR (from 4 to 40%), an increase in the SBR (from 19 to 40%), a minor improvement in spatial resolution and a similar noise level were observed in the phantom study in comparison to the standard OSEM. A decrease in the SNR, a worse spatial resolution, but only a 3 to 13% lower SBR were achieved in comparison with the vendor supplied RR algorithm. The proposed algorithm creates patient images with better contrast and lesion detectability compared to clinically used OSEM. Compared to RR, more than half of obtained images showed better contrast and nearly half of them have better lesion detectability. Conclusion: The proposed algorithm compares favorably with the standard OSEM. Although less favorable, the comparison with RR and noise suppression algorithms, suggests that it can be used with only a slight decrease in the SBR. (C) 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:858 / 864
页数:7
相关论文
共 29 条
[1]  
Bombardieri E., 2003, BONE SCINTIGRAPHY PR
[2]   A multiresolution image based approach for correction of partial volume effects in emission tomography [J].
Boussion, N ;
Hatt, M ;
Lamare, F ;
Bizais, Y ;
Turzo, A ;
Rest, CCL ;
Visvikis, D .
PHYSICS IN MEDICINE AND BIOLOGY, 2006, 51 (07) :1857-1876
[3]   Incorporation of wavelet-based denoising in iterative deconvolution for partial volume correction in whole-body PET imaging [J].
Boussion, N. ;
Le Rest, C. Cheze ;
Hatt, M. ;
Visvikis, D. .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2009, 36 (07) :1064-1075
[4]  
Cai T., 2001, SANKHYA SER B, V63, P127
[5]   Adaptive wavelet thresholding for image denoising and compression [J].
Chang, SG ;
Yu, B ;
Vetterli, M .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2000, 9 (09) :1532-1546
[6]   Image denoising with neighbour dependency and customized wavelet and threshold [J].
Chen, GY ;
Bui, TD ;
Krzyzak, A .
PATTERN RECOGNITION, 2005, 38 (01) :115-124
[8]   A COEFFICIENT OF AGREEMENT FOR NOMINAL SCALES [J].
COHEN, J .
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT, 1960, 20 (01) :37-46
[9]   Differentiation-based edge detection using the logarithmic image processing model [J].
Deng, G ;
Pinoli, JC .
JOURNAL OF MATHEMATICAL IMAGING AND VISION, 1998, 8 (02) :161-180
[10]   THE STUDY OF LOGARITHMIC IMAGE-PROCESSING MODEL AND ITS APPLICATION TO IMAGE-ENHANCEMENT [J].
DENG, G ;
CAHILL, LW ;
TOBIN, GR .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1995, 4 (04) :506-512